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Table 4 The predicted performance of trained model from RPI488 on NPInter2.0, RPI367 and RPIntDB dataset

From: IPMiner: hidden ncRNA-protein interaction sequential pattern mining with stacked autoencoder for accurate computational prediction

Dataset Organism Total # of Predicted # of
   ncRNA-protein ncRNA-protein
NPInter2.0 Homo sapiens 6,975 6,809 (97.6 %)
  Caenorhabditis elegans 36 22 (61.1 %)
  Mus musculus 2,198 2,115 (96.2 %)
  Drosophila melanogaster 91 88 (96.7 %)
  Saccharomyces cerevisiae 910 860 (94.5 %)
  Escherichia coli 202 176 (87.1 %)
  Total 10,412 10,070 (96.7 %)
RPI367 Homo sapiens 148 132 (89.2 %)
  Caenorhabditis elegans 2 2 (100.0 %)
  Mus musculus 46 34 (73.9 %)
  Drosophila melanogaster 26 24 (92.3 %)
  Saccharomyces cerevisiae 119 117 (98.3 %)
  Escherichia coli 25 21 (84.0 %)
  Total 366 330 (90.1 %)
RPIntDB Total 44,586 38,522 (86.4 %)
  1. For NPInter2.0, RPI-Pred can predict 90 % of total interactions [13]. If proteins and RNAs in a pair are obsolete, then this pair will be removed. For example, in RPI367, protein O16646 is obsolete in UniProtKB, and ncRNA u1136 interacts with O16646, this pair was removed in RPI367. In RPIntDB, there is no organism information for some interaction pairs, so we only report the total prediction accuracy